土壌の温度は作物における害虫の広がりを予測することができる(Soil Temperature Can Predict Pest Spread in Crops)

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2022-09-05 ノースカロライナ州立大学(NCState)

ノースカロライナ州立大学の新しい研究によると、トウモロコシ、綿、大豆、ピーマン、トマト、その他の野菜作物を荒らす重要な害虫であるコーンイヤーワーム(Helicoverpa zea)の蔓延を効果的に監視・予測するために土壌温度を使用することができることが示された。
研究者らは、過去の土壌温度データと長期的なコーンイヤーワームのモニタリングデータ、および害虫が寒さの中でどのように生き延びるかに関する情報を実験室で組み合わせ、「越冬成功」、つまり害虫が冬の寒い時期に地中でどれだけ生き延びることができるかについてより深く理解することに成功した。
この害虫は長距離を移動することができるため、越冬の成功率が高ければ高いほど、生息・繁殖可能な地域が広がることになる。
研究者達は、3つの異なるデータを重ね合わせ、害虫が冬の間生き残る「南方範囲」、害虫が一般的に冬の間生き残れない「北方限界」、害虫が冬の間生き残れるかどうかわからない北方と南方の間の「移行地帯」という3つの関連する地理的ゾーンを示す独自の地図を考案した。
この3つのゾーンでコーンイヤーワームの過去の傾向を示し、さらにモデルを使って今世紀末までの害虫の広がりについて予測を立てました。驚くべきことに、サザン・レンジは1981年以来3%成長している。モデルによると、サザン・レンジは今世紀末までに2倍の大きさになり、かなり北に移動し、他の2つのゾーンは縮小することが予想される。

<関連情報>

Soil Temperature Can Predict Pest Spread in Crops
Researchers use historical soil temperature data to learn about - and predict - overwintering success of the nasty corn earworm.

 

害虫の個体数動態は大陸の越冬勾配と関係がある Pest population dynamics are related to a continental overwintering gradient

Douglas Lawton, Anders S Huseth, George G Kennedy, Amy C Morey, William D Hutchison, Dominic D Reisig, Seth Dorman, DeShae Dillard, Robert C Venette, Russell L Grove, John J Adamczyk, Izailda Barbosa Dos Santos, Tracey Baute, Sebe Brown, Eric Burkness, Ashley Dean, Galen P Dively, Helene B Doughty, Shelby J Fleischer, Jessica Green, Jeremy K Greene, Krista Hamilton, Erin Hodgson, Thomas Hunt, David Kerns, Billy Rogers Leonard, Sean Malone, Fred Musser, David Owens, John C Palumbo, Silvana Paula-Moraes, Julie A Peterson, Ricardo Ramirez, Silvia I. Rondon, Abby Seaman, Tracy L Schilder, Lori Spear, Scott D Stewart, Sally Taylor, Tyler Towles, Celeste Welty, Joanne Whalen, Robert Wright, Marion Zuefle
Proceedings of the National Academy of Sciences  Published: Sept. 6, 2022
DOI: https://doi.org/10.1073/pnas.2203230119

Significance

The expansion of pest ranges due to climate change will threaten global agriculture. Winter soil temperature is known to limit pest persistence at higher latitudes. However, few studies have connected overwintering success of soil-dwelling insects with long-term population datasets to investigate how climate change may affect pests’ distributions and population dynamics in the future. Here, we present models demonstrating how greater overwintering survival may expand the range of a serious insect pest. We also highlight the need for projected soil temperature data based on climate change scenarios. To ensure sustainable agricultural production, it is imperative that insect pest range shifts are anticipated to develop solutions that mitigate crop loss in expansion areas.

Abstract

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests.
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